Hunting malware with metadata

In this post, we want to illustrate how VirusTotal (retro) hunting can be leveraged to extract malware samples and metadata linked to a single threat actor. We use the power of YARA rules to pinpoint the metadata we are looking for.

With some of the metadata extracted from the .LNK file we wrote about in our previous blog post (Volume ID and MAC address), we’re going to search on VirusTotal for samples with that metadata. It is clear from the MAC address 00:0C:29:5A:39:04 that the threat actor used a virtual machine to build malware: 00:0C:29 is an OUI owned by VMware. We wonder if the same VM was used to create other samples.
With a VirusTotal Intelligence subscription, one can search through the VirusTotal sample database, for example with YARA rules. We use the following YARA rule for the metadata:

VTI supports hunting and retro-hunting with YARA rules. With hunting, you will be informed each time your YARA rules triggers on the VT servers each time a newly submitted sample matching your rule. With retro-hunting, YARA rules are used to scan through 75TB of samples in the VT database. This correspond more or less to the set of samples submitted in the last three months.
Here is the result from a retro-hunt using YARA rule MALDOC_LNK:

Next step is to download and analyse all these samples. Since we did not include a file type condition in our YARA rule, we get different types of files: Word .doc files, .lnk files, raw OLE streams containing .lnk files, and MIME files (e-mails with Word documents as attachment).
With this command we search for strings containing “http” in the samples:

So we see that the same virtual machine has been used to created several samples. Here we extract the commands launched via the .lnk file:

There are 2 types of commands: downloading one executable; and downloading one executable and a decoy document.

The metadata from the OLE files reveals that the virtual machine has been used for a couple of weeks:

Conclusion

With metadata and VirusTotal, it is possible to identify samples created by the same actor over a period of 3 months. These samples can provide new metadata and IOCs.